With the increasing popularity of computers and computer networks, the Internet has penetrated various aspects of work, study and daily life. The development of the network brings convenience as well as various challenges to people. For example, the use of automatons illegally consumes huge network resources, for example to send mass spams, thereby lowering the efficiency of the server. In another example, certain programs are used to continuously send out service request responses to break down the server by saturation attacks. In still another example, brute-force means is taken to maliciously crack passwords. In order to prevent the above malicious behaviors, it is essential to design a tool that enables the computer to automatically distinguish whether information comes from legitimate users or the maliciously used automaton programs.
Presently, Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) codes are typically employed to distinguish whether a network user is a program or human being. The CAPTCHA code is represented by an image containing a string. In authenticating the CAPTCHA code, the user is required to input the string. The string is typically formed by uppercase and lowercase letters, and digits. Some CAPTCHA code may contain Chinese characters or a mathematical formula. The length of the string may be variable or constant. In order to prevent the CAPTCHA code from being automatically recognized by the automaton, the background of the image modified, for example by adding a texture pattern to the background of the image, to interfere the automatic recognition of the automaton.
However, once enough samples are collected, and the collected samples are learned by the automaton via a character recognizing technology to train the automaton, a computer program can be developed to decode the CAPTCHA codes. Even the improved CAPTCHA codes can also be recognized by the automaton if the library of the backgrounds of the images is not abundant enough. Therefore, the conventional CAPTCHA code cannot avoid thus problem. Taking a CAPTCHA code containing characters as an example, maximum 62 characters can be used if the uppercase and lowercase letters and digits are available for the CAPTCHA code. Therefore, the conventional CAPTCHA codes have poor anti-decryption ability and low security.
In order to improve the anti-decryption ability of the CAPTCHA codes, a clicking type CAPTCHA code (a password of which is inputted by clicking) emerges. In the use of the clicking type CAPTCHA code, a plurality of images each showing a natural object and prompt information related to content of the images are presented, so that the user is allowed to select among the images according to the prompt information by clicking, and the user identity can be verified according to the selection made by the user. The difficulty for decrypting the clicking type CAPTCHA code is dramatically increased because it is difficult for the automaton to understand the prompt information and to classify the natural objects.
However, when the clicking type CAPTCHA code is used, a number of images are delivered from the server at one time. Further, during the authentication based on the clicking type CAPTCHA code, the server may receive more than one CAPTCHA code acquiring request from the user equipment, thus causing a high workload to the server and also negatively affecting identity authentication efficiency.